Variational Technique Research Articles

Prospects and challenges of online pharmacy in post-Covid world: A qualitative study of pharmacists' experiences in Ghana

BackgroundOnline pharmacies continue to grow worldwide, especially in the wake of the COVID-19 pandemic. Ghana is experiencing this growth in an unprecedented way since its government initiated an online pharmacy pilot in December 2021, which was followed by the launch of the National Electronic Pharmacy Platform in July 2022. This pioneering initiative calls for extensive research with pharmacists to gain their perspectives. However, there is a dearth of such studies in the sub-Saharan African countries. ObjectiveThis study sought to understand how pharmacists in Ghana perceive online pharmacies in terms of the larger socio-cultural and policy implications, as well as the challenges they face in its implementation. MethodsUsing a qualitative research design, local licensed pharmacists were recruited through purposive sampling and by specifically combining the maximum variation and snowball sample techniques. Semi-structured interviews were conducted virtually with 21 pharmacists over the months of February and March 2022. The data were analyzed by using interpretive thematic analysis. ResultsPharmacists perceived that online pharmacies would transform the pharmaceutical industry in Ghana by making it convenient for people to access medication easily and at a reasonable price, while also offering them privacy. However, concerns were expressed around existing poor infrastructure and inequities, low health literacy, and inadequate regulatory practices that could pose major challenges in the operation of this platform. Engagement of stakeholders was deemed essential for success. ConclusionOnline pharmacy in Ghana and much of the developing world has the potential to transform and advance the pharmaceutical industry to better serve people. However, it could also lead to increased and irrational use of medications, if not properly regulated. Government, policy makers, and leaders in the field of digital health and pharmacy must also address poor infrastructure and inequities in digital access.

Identifying invariant solutions of wall-bounded three-dimensional shear flows using robust adjoint-based variational techniques

Identifying invariant solutions of wall-bounded three-dimensional shear flows using robust adjoint-based variational techniques

On the semiconductor to metal transition in a quantum wire: Influence of geometry and laser

The diamagnetic susceptibility and binding energy (BE) of a hydrogenic donor confined in a GaAs/AlGaAs QWW were theoretically studied in this paper under the influences of the applied laser field, QWW geometry, and non-parabolicity using variation technique combined with effective mass approximation. In the first part, the diamagnetic susceptibility and BE of the donor at the ground state are studied as a function of the size of the QWW, geometry, and applied laser field. The results reveal that changing the geometry of QWW enhances the quantum confinement effects. However, increasing the laser field reduces the BE by adding screening effects to the Coulomb interactions. Further, the diamagnetic susceptibility is available with the stability information about the carrier–parent donor system based on the mean square separation between them. It also demonstrates that susceptibility may remain stable regardless of the change in geometry and applied laser field. Thus, the diamagnetic behavior can serve as a better tool to evaluate the stability and Mott transition of donors in QWW. In the second section, the consequences of laser field and geometry on the SMT of confined donors in QWW have been studied. It is observed that the BE of donors remains constant until [Formula: see text] cm[Formula: see text] beyond which it starts to decrease gradually and vanishes exactly at critical concentration ([Formula: see text]. However, the diamagnetic susceptibility of the donor has remained constant until reaching [Formula: see text], beyond which it turned into a drastic fall, which manifested the SMT in the system. The current work is expected to add a few noteworthy points to the SMT phenomena in nanostructures.

Variational Barycentric Coordinates

We propose a variational technique to optimize for generalized barycentric coordinates that offers additional control compared to existing models. Prior work represents barycentric coordinates using meshes or closed-form formulae, in practice limiting the choice of objective function. In contrast, we directly parameterize the continuous function that maps any coordinate in a polytope's interior to its barycentric coordinates using a neural field. This formulation is enabled by our theoretical characterization of barycentric coordinates, which allows us to construct neural fields that parameterize the entire function class of valid coordinates. We demonstrate the flexibility of our model using a variety of objective functions, including multiple smoothness and deformation-aware energies; as a side contribution, we also present mathematically-justified means of measuring and minimizing objectives like total variation on discontinuous neural fields. We offer a practical acceleration strategy, present a thorough validation of our algorithm, and demonstrate several applications.

The impact of Indian radar and lightning data assimilation on the short‐range forecasts of heavy rainfall events

AbstractThe accurate prediction of high‐impact weather systems using cloud‐resolving models is still a challenge among researchers. This study evaluates the consistency of the combination of the three‐dimensional variational technique within the Gridpoint Statistical Interpolation assimilation system (GSI‐3DVAR) and nudging in the same modelling system on short‐range forecasts of three heavy rainfall events from the southwest monsoon season of 2021 over the Indian subcontinent. Three experiments have been conducted (i) control (CNTL): assimilated conventional and satellite observations; (ii) radar and lightning data assimilation (RLDA): assimilated radar reflectivity and lightning proxy reflectivity data along with all observations used in CNTL; and (iii) lightning data assimilation (LDA): same as RLDA but without the assimilation of radar data; particularly done to test the impact of assimilation of only lightning data. The model‐simulated rainfall is evaluated by using the Integrated Multi‐Satellite Retrievals (IMERG) for Global Precipitation Measurement (GPM IMERG) rainfall data. The intercomparison of LDA and RLDA for event 1 highlighted that both represent the convective regions reasonably better than CNTL, but RLDA outperforms LDA and thus further assimilation experiments are done with RLDA. RLDA provided reasonably accurate forecasts compared to CNTL, which is evident in the spatial distribution of rainfall and area‐averaged three‐hourly accumulated rainfall. Verification metrics for the three selected heavy rainfall events reveal that an optimal forecast performance (especially in the first six hours of free forecast) is obtained by the simulation with assimilation of radar and lightning data during the pre‐forecast period, through correcting the position and timing of convective centres. The probability of detection (POD) values are higher for light rainfall categories than for the heavy rain categories. POD values were higher in RLDA than CNTL throughout simulation for all three events. For all these three selected events, fractions skill scores (FSS) of RLDA are always better than CNTL with different neighbourhood sizes for different threshold values throughout the forecast period.

IBC-Oxford University2023_BJSPoster_14Short-Term Outcomes of Single-Anastomosis Sleeve-Ileal Bypass (SASI)

Abstract Background The SASI bypass, which is a simplified version of sleeve gastrectomy with transit bipartition, is based on the same metabolic principles, particularly the early postprandial ileal brake. Compared to SASI bypass, sleeve gastrectomy offers advantages such as shorter operation time and lower incidence of internal herniation. The aim of this study was to assess the safety and outcomes of SASI bypass over a 3-year follow-up period. Methods A retrospective study was conducted on all patients who underwent SASI bypass between January 2018 and June 2023. The primary endpoints were weight loss and diabetic remission. Results A total of 54 patients, with a mean age of 39,4 ± 15 years and a mean body mass index of 38,5 ± 6,8 kg/m2, underwent SASI bypass. There was no significant early postoperative complications. At the end of the first year, the average percentage of excess weight loss (%EWL) was 82,6 ± 7,4, and the rate of diabetic remission was 96,1 %. After 3 years, the %EWL was 97,4 ± 4,1, and the diabetic remission rate was 98,8%. Severe protein-energy malnutrition occurred in 4 patients(7,4%), and reversal of the bypass were made in 3 of 4 patients. Technical variations did not significantly affect %EWL or diabetic remission. Conclusion SASI bypass demonstrated promising outcomes in terms of 3-year %EWL and diabetic remission. While the double-outlet for gastric content allows access to the duodenum, it may hinder the standardization of postoperative care. Furthermore, the presence of a double-outlet does not guarantee the absence of malnutrition.

Which is the best option?: An updated review of the most widely used technical variations in entero-enteric anastomosis to minimise delayed gastric emptying after partial pancreatoduodenectomy

Which is the best option?: An updated review of the most widely used technical variations in entero-enteric anastomosis to minimise delayed gastric emptying after partial pancreatoduodenectomy

Information Bottleneck and Aggregated Learning.

We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we associate with this classification problem a representation learning problem, which we call "IB learning". We show that IB learning is, in fact, equivalent to a special class of the quantization problem. The classical results in rate-distortion theory then suggest that IB learning can benefit from a "vector quantization" approach, namely, simultaneously learning the representations of multiple input objects. Such an approach assisted with some variational techniques, result in a novel learning framework, "Aggregated Learning", for classification with neural network models. In this framework, several objects are jointly classified by a single neural network. The effectiveness of this framework is verified through extensive experiments on standard image recognition and text classification tasks.

Design and Implementation of A LED Driver Circuit with Dimming Function without Burst Mode at Constant Switching Frequency

This paper presents a dimmable LED driver with a topology of combination of series and parallel resonant converter. In dimming operation, a variable resonant inductor controlled by a PWM signal at a low frequency, while proving DC output current approaches, switching frequency variation or conventional PWM technique is not used. The proposed technique is performed on a load that consists of 40 one-watt power LEDs connected in series. Switching frequency of circuit is kept constant at 60 kHz. According to experiments results, LEDs can be dimmed to a desired power level linearly within the range of nominal power to very low power without being in burst mode unlike of the conventional PWM technique.

DRIP: deep regularizers for inverse problems

In this paper we consider inverse problems that are mathematically ill-posed. That is, given some (noisy) data, there is more than one solution that approximately fits the data. In recent years, deep neural techniques that find the most appropriate solution, in the sense that it contains a-priori information, were developed. However, they suffer from several shortcomings. First, most techniques cannot guarantee that the solution fits the data at inference. Second, while the derivation of the techniques is inspired by the existence of a valid scalar regularization function, such techniques do not in practice rely on such a function, and therefore veer away from classical variational techniques. In this work we introduce a new family of neural regularizers for the solution of inverse problems. These regularizers are based on a variational formulation and are guaranteed to fit the data. We demonstrate their use on a number of highly ill-posed problems, from image deblurring to limited angle tomography.

The influence of screening function on exciton mott transition in an asymmetric double quantum well

The semiconductor-to-metal transition (SMT) due to excitons exciton mott transition (EMT) in GaAs/Al[Formula: see text]Ga[Formula: see text]As asymmetric double quantum well (ADQW) has been studied theoretically by tuning direct (DX) and indirect (IDX) exciton densities using variation technique combined with the Monte Carlo approximation. The interaction of the optically pumped exciton densities is accounted for through the Thomas–Fermi (TF) dielectric screening and compared with Hartree–Fock (HF) screening. The screening effects of IDX at the barrier regime have been accounted for through size-dependent screening. The important characteristics of EMT, such as (i). binding energy and (ii), diamagnetic susceptibility have been studied in both coupled ([Formula: see text]Å) and isolated ([Formula: see text]Å) regimes of ADQW. The effect of asymmetry on the EMT of DX (IDX) is significant only for [Formula: see text] in the case of the coupled regime of ADQW, which may be due to the dynamic tunneling mechanism. The impact of the screening among the exciton densities to bring out the avalanche breakdown of excitons at the critical concentration has been studied for different kinds of excitons.

Expansion of a mechano-chemical plant for remanufacturing waste tires into rubber sheet and profitable wire steel by-products: A quantitative sustainability assessment

Existing mechano-chemical plants remanufacture waste tires into rubber sheet and recover nylon fibers and metal wires. As a novel expansion of this process to improve its profitability and sustainability, this study proposes the integration of a pyrolysis–distillation system to produce energy products and machinery to produce by-products from the waste steel, such as galvanized wire, nails, and crimped mesh. A quantitative analysis was performed to evaluate the amount of steel wire, energy, and CO2 emissions saved by the proposed process. Furthermore, the potential profit was calculated at low and high potential scales, representing sustainable national and international development, respectively, with the aim of establishing a circular economy. Twenty-four alternatives based on technical variations were developed and their technical feasibility and potential profit were evaluated and ranked, providing valuable information for decision makers selecting plant layout options. The economic, environmental, and technical feasibility indexes were calculated and used to specify the social feasibility index. Finally, a quadrilateral-bottom-line sustainability development approach was used to calculate the final sustainability index, showing that the proposed integration is indeed a sustainable business approach. The findings of this study prove that there are significant benefits in expanding existing remanufacturing plants to extract value from the many different materials in waste tires.

Technical advances and variations of POEM

Technical advances and variations of POEM

A systematic review and meta-regression analysis of technical efficiency in Ethiopian wheat farming

Replications are important for science, both statistically and philosophically. A plethora of empirical studies that have been done so far show that there are always variations, errors and inconclusive findings on the technical efficiency (TE) scores of wheat output in Ethiopia. In this study, we intend to contribute to these controversies by providing the first thorough investigation of the magnitude of mean-effect size and the underlying factors of mean technical efficiency variations in wheat production across studies in Ethiopia. These efficiency scores are retrieved from 31 studies, or a household size of 12,754 over the years 2011–2022. The analysis of meta-regression was done using a random effect model using Comprehensive Meta-analysis (CMA-4) software. The Begg and Mazumdar rank-correlation test, egger test, and funnel plot were used to determine publication bias across studies. Since 2022, we have utilized the classic fail-safe-N test. One issue with publication bias is the omission of some non-significant studies from the analysis, which, if they were included, would cancel out the observed effect. Further, the missing study problem or “file drawer” problem, of the study would also be computed using the “Trim and Fill” estimation approach. To evaluate heterogeneity, a forest plot is used. The effect size is also determined using the random effect model along with the I-squared statistic, the tau-squared and tau, and the Q-test. As a result, a mean effect size of 71.6% with a 95% confidence interval of 67.9%−75.3% is observed. The meta-regression demonstrates that the 31 mean technical efficiency studies included in the research had varying efficiency scores due to variations in sample size, methodologies used, publication status, and study range. It suggests that, with all other factors held constant, a 1% change in these regressors causes a 0.01%, 10.88%, 21.22%, and 6.74% change, respectively, in the mean technical efficiency scores across studies in Ethiopia. In addition, the technical efficiency score across studies is also affected by the location in which the study is conducted.

Size-Dependent Frequency Analysis of Higher-Order Microplates with FGP Core and Polymeric CNTRC Faces Considering Piezoelectricity

The present study examines a microplate with a porous structure and two nanocomposite piezoelectric layers. All the layers’ properties are graded functionally, bonded to each other, and supported by an elastic foundation that can withstand both normal and shear loads. Additionally, carbon nanotubes are used to increase the electro-mechanical performance of the piezoelectric patches, which are exposed to an externally applied electric voltage. Using a higher-order trigonometric shear deformation theory and von Karman’s assumptions, the kinematic relations are demonstrated. The governing motion equations are derived using Hamilton’s principle and variational technique, and the modified couple stress theory is employed to take the scale effect into account. An analytical method based on Fourier series functions is used to solve the differential motion equations, and the impact of diverse factors such as porosity percentage, pore distribution patterns, carbon nanotubes distribution patterns, and other key parameters on the normalized frequencies of the model is analyzed after verifying the accuracy of the results. The findings of this research may aid in the development and production of smart structures and devices with increased efficiency.

Multi-Hypothesis Marginal Multi-Target Bayes Filter for a Heavy-Tailed Observation Noise

A multi-hypothesis marginal multi-target Bayes filter for heavy-tailed observation noise is proposed to track multiple targets in the presence of clutter, missed detection, and target appearing and disappearing. The proposed filter propagates the existence probabilities and probability density functions (PDFs) of targets in the filter recursion. It uses the Student’s t distribution to model the heavy-tailed non-Gaussian observation noise, and employs the variational Bayes technique to acquire the approximate distributions of individual targets. K-best hypotheses, obtained by minimizing the negative log-generalized-likelihood ratio, are used to establish the existence probabilities and PDFs of targets in the filter recursion. Experimental results indicate that the proposed filter achieves better tracking performance than other filters.

The Peripheral Blood Stem Cell Immunome Demonstrates Abnormal Immune Effector Cells Early in the Disease Course of Multiple Myeloma and Contributes to Inferior Outcomes and Secondary Myeloid Neoplasms

Background: Upfront autologous stem cell transplant (ASCT) is the standard-of-care for newly diagnosed multiple myeloma (MM) patients. However, relapse and the development of therapy-related myeloid neoplasms (t-MN) post ASCT results in considerable morbidity and mortality. We hypothesized that enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in peripheral blood stem cells (PBSCs) of patients with MM is associated with a higher risk of relapse and development of t-MN. Methods: After institutional review board approval, we screened patients with active MM that were evaluated at Mayo Clinic, Rochester, MN between 01/01/2003 and 12/31/2020. Patients that underwent an ASCT and had cryopreserved PBSC product available for research were included. Using mass cytometry, we performed a comprehensive immunophenotyping of mobilized cryopreserved PBSCs from 54 MM patients undergoing 1 st ASCT, using validated antibody panel of 37 lymphoid- and myeloid-based markers each. Flow cytometry standard files were normalized and concatenated using the Fluidigm acquisition software. Flow cytometry standard files were uploaded to the OMIQ software from Dotmatics (www.omiq.ai, www.dotmatics.com), where transformation and cleaning (doublets, debris) were performed. To correct for between-sample technical variations (“batch effects”), we used fdaNorm within the omiq.ai platform. Clustering and visualization of normalized and concatenaded flowcytometry files were performed within the omiq.ai platform using PhenoGraph and UMAP, respectively. We performed principal component analysis (PCA) to identify major immunomic drivers of variability across patients. We explored the associations between immune subsets and the dichotomized clinical outcomes of interest: progression-free (PFS), myeloid neoplasm-free (MNFS) and overall survival (OS) from ASCT. A 2-sided false discovery rate adjusted P-value of <0.05 was considered significant when multiple comparisons were performed; otherwise, a P-value of <0.05 was considered significant. Results: The most abundant cell populations were T-cells (49% of the CD45 +) and myeloid cells (43% of the CD45 + cells). Clustering on the CD45 + cells revealed 30 unique lymphoid clusters and 27 unique myeloid clusters. Subclustering on NK-cells identified an additional 16 NK-cell clusters. On PCA, principal components-1 (PC-1) and 2 (PC-2) explained 15.2% and 12.5% of the variability in the data, respectively. A high PC-2 score was associated with inferior median PFS (20 vs. 52 months; P=0.005, Figure 1A), MNFS (52 vs. 85 months, P=0.03, Figure 1B) and OS (64 vs. 106 months, P=0.01) from ASCT. Immune subsets enriched in the high PC-2 cohort included the ‘NKT-like’ (CD56 +) T-cell subset which expressed the inhibitory CD159a receptor and TIGIT; a terminally differentiated (CD27/CD28 -, CD57/KLRG1 +) and exhausted (TIGIT/PD-1 +) T cell subset, 2 exhausted (TIGIT/PD-1 +) T cell subsets; an immunosenescent (CD27/CD28 -, CD57/KLRG1 +) T cell subset as well as a terminally exhausted (C27/C28 -, KLRG1/PD-1/TIGIT +) TCRgamma-delta subset. Immune subsets with high loadings within PC-1 (associated with improved clinical outcomes) consisted exclusively of CD4 + cells with early memory phenotypes (CD27/CD28/CD127 +). Abnormal expression of CD7 and HLA-DR expression on myeloid progenitor cell subsets was associated with an inferior PFS, MNFS, and OS. A NK-cell subcluster, characterized by an immature (CD56 high), inhibitory (CD159a +, NKG2A) phenotype, was enriched in patients developing t-MN (0.33% vs. 0.17%, P=0.006). Conclusion: We identify abnormal myeloid and immune effector cells in the PBSCs of patients with MM, even prior to ASCT. Patients with a PBSC product that is enriched in immunosuppressive T and myeloid cell subsets, and with a lower proportion of antigen presenting cells, progenitor populations, and anti-tumor macrophages have a shorter PFS and MNFS. This suggests that the predisposition to t-MN and inferior outcomes for MM are possibly determined early in the disease course. These findings need external validation and have the potential to guide sequencing of future treatment modalities.

Oropharyngeal free flap reconstruction: Transoral robotic surgery versus open approach.

Transoral robotic surgery (TORS) has evolved since its 2009 US Food and Drug Administration approval for use in local stage T1-T2 oropharyngeal carcinoma. The ability to resect increasingly larger and more complex lesions has led to the need to introduce reconstructive techniques through this route, avoiding the classic transmandibular or pull-through approach. Few studies have compared the safety, efficacy, and advantages of TORS versus classic open approaches in oropharyngeal salvage surgery with reconstruction using microanastomosed flaps. Here we retrospectively compare our center's experience with the open approach and TORS and describe the technical variations used. Between 2013 and 2021, 30 stage III-IV oropharyngeal cancer patients underwent salvage surgery with reconstruction in our center. From 2013 to 2017, 15 patients underwent surgery with the classic open approach, and from 2018 to 2021, an additional 15 patients underwent TORS. We have compared surgical outcomes, post-surgical results, and survival in the two groups. Patient characteristics were similar in the two groups. TORS was associated with shorter surgical time (p < .001), fewer complications (p = .01), shorter hospital stay (p < .001), and lower feeding tube requirements (p = .003). No significant differences were observed between the two groups in the free margin rate or survival. Oropharyngeal salvage surgery with TORS with free flap reconstruction reduced associated morbidity compared to the open approach in a patient cohort with poor prognosis. 4.

Folk Song "Sorrow After Sorrow" In The Works Of Borys Liatoshynsky: Intonation And Semantic Analysis

Relevance of research. Borys Lyatoshynsky (1895–1968) is one of the most outstanding composers of the last century. Many studies have been devoted to the study of his work in various aspects, although this topic remains incomplete and relevant. A manifestation of the composer's national thinking is, among other things, his use of folk melodies as the basis of thematism. A comparison of the composer's methods of working with folk song material in different genres has not yet been the subject of a special scientific study.&#x0D; The purpose of the study: to investigate the process of rethinking the folk song "Sorrow after Sorrow" in Lyatoshynsky's works, to consider and compare the principles of the composer's work on the folk melody in the genres of arrangement and symphony.&#x0D; Methods. The comparative, historical methods, as well as methods of genre-style, semantic and intonation analysis were used.&#x0D; The results and conclusions. The article analyses B. Liatoshynsky's approaches to working with folk song material using examples of works in which the composer refers to the folk song "Sorrow after Sorrow". The principles of processing this folklore sample in the genre of folk song arrangement for voice and piano are highlighted in the context of the evolution of the genre and in relation to the traditions established in Ukrainian music. The commonality of the basic methods of folk song arrangement in the works of M. Leontovych and B. Liatoshynsky is substantiated—the inviolability of the chant as a carrier of the intonation-semantic idea of the work, the usage of the latest compositional techniques of harmonic and textural variation, the development of the most expressive motifs in the accompanying voices or instrumental part, the construction of a through(endto-end) musical dramaturgy that pushes the limits of the original strophicity, the introduction of conceptuality and symphonic thinking into the genre. The place and role of the folk song melody "Sorrow after Sorrow" in the Third Symphony of B. Liatoshynsky is considered, the process of its involvement into the complex symphonic development is characterized: the inclusion of the theme into the leitmotif system of the symphonic cycle, the usage of intonational variation techniques, methods of timbral dramaturgy, polyphonic and motivic development in relation to the theme, due to which the theme appears in various figurative and emotional gradations, undergoes significant changes up to its transformation (the principle of monothemism).&#x0D; Conclusions are made regarding the continuity of the stages of working with the folklore primary source in the researched works of Liatoshynsky: in the genre of arrangement, a peculiar adaptation of the folk song sample to the field of academic music takes place, in the process of its compositional development, the intonational-semantic core—the motif of regret—is distinguished. At the next stage, this motif becomes the basis for a complex figurative and thematic development and author’s reinterpretation in works of other genres, an impetus for the implementation of significant symphonic concepts.

Nonclassical Parametric Variational Technique to Manipulability Control of a Serial-Link Robot That Is Used in Treatment of Femoral Shaft Fractures

Robot-assisted intramedullary nailing is a minimally invasive surgical procedure commonly used to treat femur fractures. Despite its benefits, there are several disadvantages associated with this technique, such as frequent malalignment, physical fatigue, and excessive radiation exposure for medical personnel. Therefore, it is crucial to ensure that robotic surgery for fracture reduction is precise and safe. Precise calculation and regulation of the robot’s reduction force are of utmost importance. In this study, we propose a manipulator that utilises robot assistance and indirect contact with the femur to effectively reduce fractures in the shaft. The dynamics of the reduction robot are analysed using the implicit function theorem, which allows us to address the reduced problem. A parametric approach is presented to tackle the initial algebraic constraints, enabling the approximation of the state-space solution while simultaneously controlling the class of constraints in a multiway manner. This approach simplifies the problem from an infinite-dimensional one to a finite-dimensional one, leading to an approximate solution obtained by solving a set of control linear algebraic equations. The proposed robotic-assisted system enhances fracture repositioning while reducing radiation exposure for both the patient and the medical staff. Through numerical results and their practical application, we have developed an efficient method that yields positive outcomes.